AI & ML Certification Online for USA Professionals – AI/ML Programs

The table below lists some AI and ML courses offered through upGrad and their overview:

Artificial Intelligence and Machine Learning Course Eligibility & Admission Criteria

Eligibility and admission criteria for Machine Learning and Artificial Intelligence courses vary by institution.

Course Duration

Duration may vary depending on the program and the institution. For instance, the online Master of Science in Machine Learning & AI from Liverpool John Moores University is an 18-month program, whereas the Executive Diploma in Machine Learning and AI from IIIT-B is a 12-month course.

Eligibility Criteria

• A bachelor's degree with a minimum score of 50% or an equivalent CGPA is the minimum eligibility requirement

A 50% (or equivalent) mark in a bachelor's degree is the key prerequisite. Some universities may require a background in math/statistics, but it is not mandatory. Depending on the program, 1 year of experience in programming or analytics may help.

Curriculum Highlights and Specializations Available

Specialization:

1. ML Ops

• Suits those focused on AI deployment & operations.
• Future-ready curriculum: Real-time ML pipelines, multi-cloud (AWS, GCP, Azure), CI/CD, Kafka, PySpark, LLMOps with Chroma & Milvus.
• Upgraded tools: Kubernetes, FastAPI, MLflow, SageMaker.
• Industry projects: 12+ hands-on projects across 6+ domains.

2. Generative AI

• Suits those looking to build a career with Generative AI.
• Future-ready curriculum: Advanced ML/DL, GenAI, multimodal LLMs, agentic systems.
• Upgraded tools: Gemini, DeepSeek, Claude, CreAI, Ollama, LangGraph, Imagen, Autogen.
• Industry projects: 12+ projects in 5+ domains.

Real-World Applications of AI and ML

• AI in finance for fraud detection, credit risk evaluation, and algorithmic trading.
• Healthcare uses ML for predictive diagnostics and medical image analysis.
• Retail leverages AI for customer segmentation, demand forecasting, and personalized recommendations.
• Logistics and transportation use ML for route optimization, inventory management, and supply chain improvement.
• Brands use AI and natural language processing to enhance marketing targeting, sentiment analysis, and consumer behavior predictions.

Hands-On Projects and Industry Collaborations

• Authentic datasets from finance, healthcare, retail, and social media for real-world learning.
• Use of technologies like Python, TensorFlow, PyTorch, Scikit-learn, and cloud services (AWS, Azure, GCP).
• End-to-end project development including data collection, preprocessing, modeling, and evaluation.
• Team projects and case studies provide practical industry experience.

• Programs are offered in collaboration with globally recognized universities on the upGrad platform.
• Learners work on USA-focused projects.
• Personalized mentorship is offered.
• Machine Learning, Deep Learning, Natural Language Processing, MLOps, and Generative AI are all covered within the program’s broad scope.
• Over 60 case studies combined with 80+ programming tools and Generative AI.
• Each learner can choose one of the two specializations offered: MLOps or Generative AI.
• Capstone projects are tailored to your domain.
• All first-time learners receive a 3-month programming bootcamp.
• Upon completing the course, learners become graduates of IIIT Bangalore.
• Flexible online learning designed especially for working professionals.
• Over 500 hours of learning, setup, and building industry projects for your resume.
• Learn specialized modules and advanced tools in Generative AI, including LangChain and LLMs.
• The program is supported by the academic legacy of IIIT Bangalore and global expertise from LJMU, with a network of 10,000+ alumni.
• Choose from 15+ industry projects.
• Optional on-campus immersion available.

As demand for AI and ML professionals increases across the United States, selecting the right course can give you an advantage in the job market. The ideal program will provide opportunities for practical experience, flexibility to fit your schedule and career aspirations, and strong career assistance.

What to Look for:

• Accreditation from Reputable Institutions: Choose programs accredited by respected U.S. universities or globally accredited institutions to ensure your credentials are recognized by employers.
• Comprehensive Curriculum: Ensure the course covers supervised and unsupervised learning, along with advanced topics such as deep learning, MLOps, and Generative AI.
• Hands-on Experience: Look for programs that offer real-world projects, case studies, and exposure to industry tools like Python, TensorFlow, and PyTorch.
• Mentorship and Support: Check whether the course provides experienced faculty, live sessions, and 1-on-1 mentoring.
• Career Support and Flexibility: Opt for programs that assist with resume building and interview preparation and offer flexible online formats suitable for working professionals in the U.S.

Is it worth learning machine learning in the USA?

Pursuing machine learning in the USA is worthwhile due to ongoing demand, strong salary potential, and significant career growth opportunities in ML and AI across various industries. The field is rapidly expanding, offering a chance to work on cutting-edge technology and take on strategic, impactful roles.

What are the prerequisites for enrolling in AI and machine learning courses in the USA?

A minimum of 50% (or equivalent) in a bachelor's degree is the primary prerequisite for an online AI and ML course. Some universities may prefer a background in math/statistics, but it is not mandatory. Depending on the program, 1 year of experience in programming or analytics may be beneficial.

Can individuals from non-technical backgrounds pursue machine learning courses in the USA?

Yes, individuals from non-technical backgrounds can pursue machine learning courses in the USA, as many programs are beginner-friendly and designed for a wide range of learners.

Which programming language should I learn for machine learning in the USA?

Python is the best programming language to learn for machine learning in the USA due to its extensive libraries, strong community support, and ease of use. While R, Java, and C++ have specific use cases, Python is the most versatile and widely preferred.

How to prepare for a machine learning interview in the USA?

To prepare for a machine learning interview in the USA, review ML fundamentals, practice coding, gain hands-on experience with tools like Python, TensorFlow, and PyTorch, work on real-world projects, and develop strong communication and problem-solving skills.

How can AI and machine learning courses help professionals across different industries in the USA?

AI and machine learning courses help professionals by enhancing career prospects, boosting earning potential, and equipping them with skills to automate tasks, improve decision-making, and optimize business processes across industries.

What career opportunities are available after completing an AI or machine learning course in the USA?

Graduates can pursue roles such as Machine Learning Engineer, Data Scientist, AI Research Scientist, Robotics Engineer, NLP Engineer, Computer Vision Specialist, Data Analyst, Consultant, or AI Product Manager.

What are the prospects of AI and machine learning jobs in the USA?

The prospects for AI and ML jobs in the USA are strong, driven by rapid industry growth, high salaries, and increasing adoption of AI across sectors. New positions continue to emerge as technologies evolve.

What support does upGrad provide to AI and ML learners in the USA?

upGrad offers mentorship, personalized feedback, doubt resolution, resume support, interview preparation, and networking opportunities to help AI and ML learners succeed in their career goals.